CRM

Backfill Intercom conversation topics onto stale HubSpot contacts

Finds HubSpot contacts with no recent Intercom topic, pulls their conversation history from Intercom, classifies the dominant topic with OpenAI.

CategoryCRM
Enginesim
Difficultyintermediate
Triggerschedule
Steps7
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerDaily schedule fires the backfill run
  • ActionQuery HubSpot for contacts missing a fresh topicHubSpotHubSpot
  • LogicSkip contacts with no Intercom conversations
  • ActionPull recent conversation transcripts from IntercomIntercomIntercom
  • ActionClassify dominant topic with OpenAIOpenAI
  • LogicDrop low-confidence topic labels
  • OutputWrite topic + timestamp to HubSpot contactHubSpotHubSpot

What it does

Many HubSpot contacts carry no signal about what they actually talk to support about. This workflow walks contacts whose `last_intercom_topic` property is empty or older than 90 days, fetches their Intercom conversation transcripts, and uses OpenAI to label the single dominant topic (e.g. "billing dispute", "onboarding", "API integration"). The result is written back to HubSpot so segmentation and routing reflect real conversation content.

When to use it

Run this when your CRM segments are decaying because topic data was never captured, or after migrating support tooling left a backlog of un-tagged contacts. Ideal as a one-time backfill plus a monthly catch-up on stale records.

How it works

A daily schedule fires the run. The workflow queries HubSpot for contacts missing a fresh topic, then for each one pulls the last 10 Intercom conversations. A logic step skips contacts with zero conversations. OpenAI reads the merged transcripts and returns one canonical topic plus a confidence score. A filter drops low-confidence labels, and the final step patches the HubSpot contact's `last_intercom_topic` and `topic_updated_at` properties.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect HubSpotCRM, deals, marketing, support.
  2. 2
    Connect IntercomConversations, contacts, articles.
  3. 3
    Connect OpenAIModels, embeddings, files.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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